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Navigating Insurance Claim Data through Machine Learning
The increasing ability to store and analyse the data due to the advancement in technology has provided insurers opportunities in optimizing capital held by insurance companies. Often, the ability to optimize the capital would lower the cost of capital for companies, allowing the capital to be re-deployed for other purposes. This could translate into an increase in profit from the lower cost incurred or an increase in competitiveness through lowering the premiums companies charge for their insurance plans.
The machine learning technology enables insurers in building machine learning models to predict claim cost in a more tidy and efficient manner. Besides, this method also allows insurers to harass on the power of data science to mine the “gold” in unstructured data, such as claim descriptions, item descriptions, and so on. This could provide the insurers more insights from their claim data, which the insights can be used to manage claim cost and determine premium.
Technology Features, Specifications and Advantages
This technology uses machine learning approach to estimate claim cost and explain the drivers of claim cost. It also enables the insurers to tap into their unstructured data, which are conventionally not used in many insurance applications, such as premium setting, claim cost estimation and so on.
This would effectively provide the insurers a ‘tool’ to complement the conventional approach to further optimize their required capital through sharpening the claim cost estimation and assumption setting. This would allow insurers to lower the required capital without compromising the solvency of the companies.
Besides, this technology is also a crucial building block for the insurers to explore personalized pricing. Insurers would be able to price the customers more accurately depending on the riskiness of the customers. This would ensure the insurers are able to retain the “good risks” in the portfolio, improving overall profitability of the business.
This technology can used in following area within insurance functions :
- Complement conventional premium setting by providing additional pricing parameters
- Form part of the building block of personalized pricing
- Allow insurers to form strategies through the insights gathered through the analysis
- Optimize the required capital by the insurance companies
The customer benefits include, but not limited to :
- More accurate claim cost estimation
- Improve the profitability of different business lines in insurance companies
- Allow the insurers to explore personalized pricing to gain a sustainable competitive edge in this increasing competitive market
- Optimize required capital while not jeopardizing the solvency of the insurance companies